A Financial Knowledge Q&A Model for Power Enterprise Based on ChatGLM2-6B
With the continuous expansion of the scale of the power system,a significant amount of repetitive and complex tasks emerge in daily financial operations.Traditional methods of organizing and managing financial knowledge are no longer sufficient to satisfy the requirements of the current power system.With the consideration of this,the paper constructs a financial knowledge graph using the large-scale language model called ChatGLM2-6B.This method aims to standardize financial and project manage-ment processes and assist in financial decision-making.Firstly,the ChatGLM2-6B model should be optimized through instruc-tion fine-tuning and prompt learning in order to extract event and event relationship pairs from financial contracts and invoice data,respectively.Then,the event relationship pairs are then stored as a local knowledge base using the FAISS vector database,additionally,a FAISS-ERNIE similarity evaluation model is trained to enhance the capability of knowledge retrieval,which could improve the question-answering ability of ChatGLM2-6B.Finally,hierarchical clustering algorithm is employed to general-ize event relationship pairs,aiming to obtain contract knowledge graph and invoice knowledge evolutionary graph.These two graphs could be utilized to provide standardized guidance and supervision for real-time financial operations,achieving transpar-ency in financial execution.The experimental results demonstrate that the method proposed in this paper exhibits excellent perfor-mance in event extraction,event relationship pair extraction,and similarity retrieval.The constructed contract and invoice knowledge evolutionary graphs hold significant implications for financial management in power enterprises,contributing to en-hance the level of corporate management.
万方数据
维普
